Automated Calculation of Cochlear Implant Electrode Insertion Parameters in Clinical Cone-Beam CT. Issue 2 (16th November 2021)

• Record Type: Journal Article
• Authors: Andersen, Steven Arild Wuyts; Keith, Jason P.; Hittle, Brad; Riggs, William J.; Adunka, Oliver; Wiet, Gregory J.; Powell, Kimerly A.
• Is Part Of: Otology & neurotology. Volume 43:Issue 2(2022)
• Page Start: 199
• Page End: 205
• Publication Date: 2021-11-16
• Subjects: Cochlear implantation -- Image-guided programming -- Otology -- Patient-specific adaptation -- Segmentation; Otology -- Periodicals; Ear -- Diseases -- Periodicals; Skull base -- Surgery -- Periodicals; 617.8005
• DOI: 10.1097/MAO.0000000000003432
• Languages: English
• ISSNs: 1531-7129

Abstract

Abstract : Hypothesis: Automated processing of postoperative clinical cone-beam CT (CBCT) of cochlear implant (CI) patients can be used to accurately determine electrode contacts and integrated with an atlas-based mapping of cochlear microstructures to calculate modiolar distance, angular insertion distance, and scalar location of electrode contacts. Background: Hearing outcomes after CI surgery are dependent on electrode placement. CBCT is increasingly used for in-office temporal bone imaging and might be routinely used for pre- and post-surgical evaluation. Methods: Thirty-six matched pairs of pre- and postimplant CBCT scans were obtained. These were registered with an atlas to model cochlear microstructures in each dataset. Electrode contact center points were automatically determined using thresholding and electrode insertion parameters were calculated. Automated localization and calculation were compared with manual segmentation of contact center points as well as manufacturer specifications. Results: Automated electrode contact detection aligned with manufacturer specifications of spacing and our algorithms worked for both distantly- and closely spaced arrays. The average difference between the manual and the automated selection was 0.15 mm, corresponding to a 1.875 voxel difference in each plane at the scan resolution. For each case, we determined modiolar distance, angular insertion depth, and scalar location. These calculations also resulted in similar insertion values using manual and automated contact points as well as aligning with electrode properties. Conclusion: Automated processing of implanted high-resolution CBCT images can provide the clinician with key information on electrode placement. This is one step toward routine use of clinical CBCT after CI surgery to inform and guide postoperative treatment.